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Free Courses with Certificate | Microsoft | Harvard | Udacity | Coursera | Python Coding | ML | Data Science | Java Programming

We provide unlimited Free Courses with Certificate to learn Python, Data Science, Java, Web development, AI, ML, Finance, Hacking, Marketing and many more from top websites Managed by: @Guideishere12 Buy ads: https://telega.io/c/free4unow_backup

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Free Programming and Data Analytics Resources πŸ‘‡πŸ‘‡ βœ… Data science and Data Analytics Free Courses by Google https://developers.google.com/edu/python/introduction https://grow.google/intl/en_in/data-analytics-course/?tab=get-started-in-the-field https://cloud.google.com/data-science?hl=en https://developers.google.com/machine-learning/crash-course https://t.me/datasciencefun/1371 πŸ” Free Data Analytics Courses by Microsoft 1. Get started with microsoft dataanalytics https://learn.microsoft.com/en-us/training/paths/data-analytics-microsoft/ 2. Introduction to version control with git https://learn.microsoft.com/en-us/training/paths/intro-to-vc-git/ 3. Microsoft azure ai fundamentals https://learn.microsoft.com/en-us/training/paths/get-started-with-artificial-intelligence-on-azure/ πŸ€– Free AI Courses by Microsoft 1. Fundamentals of AI by Microsoft https://learn.microsoft.com/en-us/training/paths/get-started-with-artificial-intelligence-on-azure/ 2. Introduction to AI with python by Harvard. https://pll.harvard.edu/course/cs50s-introduction-artificial-intelligence-python πŸ“š Useful Resources for the Programmers Data Analyst Roadmap https://t.me/sqlspecialist/94 Free C course from Microsoft https://docs.microsoft.com/en-us/cpp/c-language/?view=msvc-170&viewFallbackFrom=vs-2019 Interactive React Native Resources https://fullstackopen.com/en/part10 Python for Data Science and ML https://t.me/datasciencefree/68 Ethical Hacking Bootcamp https://t.me/ethicalhackingtoday/3 Unity Documentation https://docs.unity3d.com/Manual/index.html Advanced Javascript concepts https://t.me/Programming_experts/72 Oops in Java https://nptel.ac.in/courses/106105224 Intro to Version control with Git https://docs.microsoft.com/en-us/learn/modules/intro-to-git/0-introduction Python Data Structure and Algorithms https://t.me/programming_guide/76 Free PowerBI course by Microsoft https://docs.microsoft.com/en-us/users/microsoftpowerplatform-5978/collections/k8xidwwnzk1em Data Structures Interview Preparation https://t.me/crackingthecodinginterview/309?single 🍻 Free Programming Courses by Microsoft ❯ JavaScript http://learn.microsoft.com/training/paths/web-development-101/ ❯ TypeScript http://learn.microsoft.com/training/paths/build-javascript-applications-typescript/ ❯ C# http://learn.microsoft.com/users/dotnet/collections/yz26f8y64n7k07 Join @free4unow_backup for more free resources. ENJOY LEARNING πŸ‘πŸ‘
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Complete Roadmap to become a web developer in two months: Week 1-2: Basics of Web Development 1. HTML & CSS: Learn the fundamentals of building web pages with HTML for structure and CSS for styling. 2. Responsive Design: Understand how to make your websites responsive to different screen sizes using media queries. 3. Basic JavaScript: Start with basic JavaScript concepts like variables, data types, and operators. Week 3-4: Intermediate Web Development 1. DOM Manipulation: Learn how to manipulate the Document Object Model (DOM) with JavaScript to dynamically change website content. 2. Intermediate JavaScript: Dive deeper into JavaScript with concepts like functions, arrays, objects, and control flow. 3. Version Control: Learn Git and GitHub for version control and collaboration. Week 5-6: Frontend Development 1. Frontend Frameworks: Learn a frontend framework like React, Vue.js, or Angular. Focus on one and understand its fundamentals. 2. Package Managers: Learn how to use npm or yarn to manage dependencies for your projects. 3. CSS Preprocessors: Explore tools like Sass or Less to enhance your CSS workflow. Week 7-8: Backend Development 1. Server-side Programming: Learn a backend language like Node.js with Express, Python with Django or Flask, or Ruby on Rails. 2. Databases: Understand basics of database management systems like MongoDB, MySQL, or PostgreSQL. 3. APIs: Learn how to build and consume APIs to connect your frontend and backend. Additional Tips: - Practice regularly by building projects. Start with simple ones and gradually increase complexity. - Utilize online resources like tutorials, documentation, and forums like Stack Overflow and GitHub. - Network with other developers through online communities and attend webinars or meetups. - Stay updated with industry trends and best practices by following blogs and podcasts. 5 Free Web Development Courses by Udacity πŸ‘‡πŸ‘‡ Intro to HTML and CSS Intro to Backend Networking for Web Developers Intro to JavaScript Object-Oriented JavaScript Free Web Development Resources: πŸ‘‡ https://t.me/webdevcoursefree Join @free4unow_backup for more free resources. ENJOY LEARNING πŸ‘πŸ‘
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Intro to HTML and CSS | Udacity

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Best way to prepare for Python interviews πŸ‘‡πŸ‘‡ 1. Fundamentals: Strengthen your understanding of Python basics, including data types, control structures, functions, and object-oriented programming concepts. 2. Data Structures and Algorithms: Familiarize yourself with common data structures (lists, dictionaries, sets, etc.) and algorithms. Practice solving coding problems on platforms like LeetCode or HackerRank. 3. Problem Solving: Develop problem-solving skills by working on real-world scenarios. Understand how to approach and solve problems efficiently using Python. 4. Libraries and Frameworks: Be well-versed in popular Python libraries and frameworks relevant to the job, such as NumPy, Pandas, Flask, or Django. Demonstrate your ability to apply these tools in practical situations. 5. Web Development (if applicable): If the position involves web development, understand web frameworks like Flask or Django. Be ready to discuss your experience in building web applications using Python. 6. Database Knowledge: Have a solid understanding of working with databases in Python. Know how to interact with databases using SQLAlchemy or Django ORM. 7. Testing and Debugging: Showcase your proficiency in writing unit tests and debugging code. Understand testing frameworks like pytest and debugging tools available in Python. 8. Version Control: Familiarize yourself with version control systems, particularly Git, and demonstrate your ability to collaborate on projects using Git. 9. Projects: Showcase relevant projects in your portfolio. Discuss the challenges you faced, solutions you implemented, and the impact of your work. 10. Soft Skills: Highlight your communication and collaboration skills. Be ready to explain your thought process and decision-making during technical discussions. Best Resource to learn Python Python Interview Questions with Answers Freecodecamp Python Course with FREE Certificate Python for Data Analysis and Visualization Python course for beginners by Microsoft Python course by Google Please give us credits while sharing: -> https://t.me/free4unow_backup ENJOY LEARNING πŸ‘πŸ‘
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Which courses do you want for free?Anonymous voting
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Complete Roadmap to learn Excel in 2024 πŸ‘‡πŸ‘‡ 1. Basic Excel Skills:    - Familiarize yourself with Excel's interface and navigation.    - Learn basic formulas (SUM, AVERAGE, COUNT, etc.).    - Understand cell referencing (absolute vs. relative). 2. Data Entry and Formatting:    - Practice entering and formatting data efficiently.    - Explore cell formatting options for a clean and organized dataset. 3. Advanced Formulas:    - Master more advanced formulas like VLOOKUP, HLOOKUP, INDEX-MATCH.    - Learn logical functions (IF, AND, OR).    - Understand array formulas for complex calculations. 4. Pivot Tables:    - Gain proficiency in creating Pivot Tables for data summarization.    - Learn to customize and format Pivot Tables effectively. 5. Data Cleaning:    - Acquire skills in cleaning and transforming data.    - Explore text-to-columns, remove duplicates, and data validation. 6. Charts and Graphs:    - Learn to create various charts (bar, line, pie) for data visualization.    - Understand chart formatting and customization. 7. Dashboard Creation:    - Combine charts and tables to build basic dashboards.    - Explore dynamic dashboards using Excel features. 8. Macros and VBA:    - Dive into basic automation using Excel macros.    - Learn Visual Basic for Applications (VBA) for more advanced automation. 9. Power Query:    - Introduce yourself to Power Query for enhanced data manipulation.    - Learn to import, transform, and load data efficiently. 10. Advanced Excel Techniques:    - Explore advanced features like Goal Seek, Solver, and Scenario Manager.    - Master the use of data tables for sensitivity analysis. 11. Real-world Projects:    - Apply your skills to real-world projects or datasets.    - Practice solving analytical problems using Excel. Remember to practice consistently, as hands-on experience is crucial for mastering Excel. This roadmap will provide a solid foundation for your journey into data analysis using Excel. 5️⃣ Free resources to practice Excel https://www.w3schools.com/EXCEL/index.php https://bit.ly/3PSorPT http://learn.microsoft.com/en-gb/training/paths/modern-analytics/ https://t.me/excel_analyst/52 https://excel-practice-online.com/ Join for more: https://t.me/free4unow_backup ENJOY LEARNING πŸ‘πŸ‘
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Here is a complete roadmap to learn Data Structures and Algorithms (DSA): πŸ‘‡πŸ‘‡ 1. Basics of Programming: Start by learning the basics of a programming language like Python, Java, or C++. Understand concepts like variables, loops, functions, and arrays. 2. Data Structures: Study fundamental data structures like arrays, linked lists, stacks, queues, trees, graphs, and hash tables. Understand the operations that can be performed on these data structures and their time complexities. 3. Algorithms: Learn common algorithms like searching, sorting, recursion, dynamic programming, greedy algorithms, and divide and conquer. Understand how these algorithms work and their time complexities. 4. Problem Solving: Practice solving coding problems on platforms like LeetCode, HackerRank, or Codeforces. Start with easy problems and gradually move to medium and hard problems. 5. Complexity Analysis: Learn how to analyze the time and space complexity of algorithms. Understand Big O notation and how to calculate the complexity of different algorithms. 6. Advanced Data Structures: Study advanced data structures like AVL trees, B-trees, tries, segment trees, and fenwick trees. Understand when and how to use these data structures in problem-solving. 7. Graph Algorithms: Learn graph traversal algorithms like BFS and DFS. Study algorithms like Dijkstra's algorithm, Bellman-Ford algorithm, and Floyd-Warshall algorithm for shortest path problems. 8. Dynamic Programming: Master dynamic programming techniques for solving complex problems efficiently. Practice solving dynamic programming problems to build your skills. 9. Practice and Review: Regularly practice coding problems and review your solutions. Analyze your mistakes and learn from them to improve your problem-solving skills. 10. Mock Interviews: Prepare for technical interviews by participating in mock interviews and solving interview-style coding problems. Practice explaining your thought process and reasoning behind your solutions. Top DSA resources to crack coding interview πŸ‘‰ GeekforGeeks πŸ‘‰ Leetcode πŸ‘‰ Hackerrank πŸ‘‰ DSA Steps πŸ‘‰ FreeCodeCamp πŸ‘‰ Best DSA Resources Share with Credits: https://t.me/free4unow_backup ENJOY LEARNING πŸ‘πŸ‘
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